# Qwen2.5-Coder-32B vs Qwen3.5-Flash

> Qwen3.5-Flash is the stronger model overall, scoring 42.3 to 32.9 on the Noometry Index.

- Canonical page: https://noometry.com/compare/qwen2-5-coder-32b-vs-qwen3-5-flash
- Last updated: 2026-10-10
- Shared benchmarks: 13

## Summary

- They share 13 benchmarks with published results for both. Qwen2.5-Coder-32B scores higher in 0 categories and Qwen3.5-Flash in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where Qwen3.5-Flash leads 58.2 to 41.8.
- Qwen3.5-Flash is cheaper at $0.10 / $0.40 per million input/output tokens, against $0.66 / $1 for Qwen2.5-Coder-32B.
- Qwen3.5-Flash accepts more context: 1M tokens versus 33K.
- Qwen2.5-Coder-32B has downloadable open weights; the other is API-only.

## Snapshot

| | Qwen2.5-Coder-32B | Qwen3.5-Flash |
|---|---|---|
| Provider | Alibaba (Qwen) | Alibaba (Qwen) |
| Noometry Index | 32.9 | 42.3 |
| Rank | 239 | 105 |
| Context | 33K | 1M |
| Input $/M | $0.66 | $0.10 |
| Output $/M | $1 | $0.40 |
| Weights | Open | Proprietary |

## Coding

- Qwen2.5-Coder-32B: 22.4 (#328)
- Qwen3.5-Flash: 33.9 (#234)

| Benchmark | Qwen2.5-Coder-32B | Qwen3.5-Flash |
|---|---|---|
| LMArena Coding | 1276 | 1412 |
| SWE-bench Verified (bash only) | 9% | — |
| Aider Polyglot | 16.4% | — |
| LMArena WebDev | — | 1243 |
| BigCodeBench Instruct | 49% | — |
| LiveBench Coding | 56.9% | — |
| BigCodeBench Complete | 58% | — |
| ALE-Bench | — | 221.8 |
| HumanEval+ | 87.2% | — |
| MBPP+ | 77% | — |

## Agentic & Tool Use

- Qwen2.5-Coder-32B: —
- Qwen3.5-Flash: —

| Benchmark | Qwen2.5-Coder-32B | Qwen3.5-Flash |
|---|---|---|
| Vending-Bench 2 | — | 462.69 |

## Reasoning

- Qwen2.5-Coder-32B: 20.4 (#220)
- Qwen3.5-Flash: 32.9 (#63)

| Benchmark | Qwen2.5-Coder-32B | Qwen3.5-Flash |
|---|---|---|
| LMArena Hard Prompts | 1251 | 1404 |
| Epoch Capabilities Index | 119.41 | 143.98 |
| Chess Puzzles | — | 21% |
| LiveBench Reasoning | 42.1% | — |
| Mystery Game Puzzles | — | 20% |
| DTBench | — | 82.9% |
| LiveBench Data Analysis | 49.9% | — |
| LMCA | — | 29.1% |
| HellaSwag | 83% | — |
| LiveBench | 46.2% | — |
| WinoGrande | 80.8% | — |

## Math

- Qwen2.5-Coder-32B: 30.8 (#203)
- Qwen3.5-Flash: 36.3 (#117)

| Benchmark | Qwen2.5-Coder-32B | Qwen3.5-Flash |
|---|---|---|
| LMArena Math | 1251 | 1407 |
| FrontierMath (Tiers 1-3) | — | 18.2% |
| OTIS Mock AIME 2024-2025 | — | 84.4% |
| LiveBench Math | 46.6% | — |
| FrontierMath (Feb 2025 set) | — | 6.2% |
| FrontierMath Tier 4 (v1) | — | 0% |
| GSM8K | 93% | — |

## Knowledge

- Qwen2.5-Coder-32B: 32.9 (#200)
- Qwen3.5-Flash: 43.2 (#84)

| Benchmark | Qwen2.5-Coder-32B | Qwen3.5-Flash |
|---|---|---|
| LMArena Expert | 1221 | 1408 |
| GPQA Diamond | — | 82.3% |
| SimpleQA Verified | — | 20.3% |
| Vectara Hallucination Rate | — | 10.5% |
| ARC (AI2) Challenge | 70.5% | — |
| MMLU | 79.1% | — |

## Multilingual

- Qwen2.5-Coder-32B: 38.0 (#230)
- Qwen3.5-Flash: 50.7 (#116)

| Benchmark | Qwen2.5-Coder-32B | Qwen3.5-Flash |
|---|---|---|
| LMArena Non-English | 1205 | 1385 |
| LMArena Chinese | 1222 | 1446 |
| LMArena Russian | 1228 | 1379 |
| LMArena French | — | 1412 |
| LMArena German | — | 1389 |
| LMArena Japanese | — | 1369 |
| LMArena Korean | — | 1344 |
| LMArena Spanish | — | 1399 |

## Instruction Following

- Qwen2.5-Coder-32B: 61.6 (#240)
- Qwen3.5-Flash: 72.8 (#133)

| Benchmark | Qwen2.5-Coder-32B | Qwen3.5-Flash |
|---|---|---|
| LMArena Instruction Following | 1223 | 1374 |
| LiveBench Instruction Following | 58.7% | — |

## Long Context

- Qwen2.5-Coder-32B: 37.9 (#204)
- Qwen3.5-Flash: 42.4 (#119)

| Benchmark | Qwen2.5-Coder-32B | Qwen3.5-Flash |
|---|---|---|
| LMArena Longer Query | 1251 | 1392 |

## Writing & Preference

- Qwen2.5-Coder-32B: 41.8 (#235)
- Qwen3.5-Flash: 58.2 (#117)

| Benchmark | Qwen2.5-Coder-32B | Qwen3.5-Flash |
|---|---|---|
| LMArena Text | 1230 | 1397 |
| LMArena Creative Writing | 1174 | 1343 |
| LMArena Multi-Turn | 1222 | 1393 |
| LiveBench Language | 23.3% | — |

## FAQ

### Is Qwen2.5-Coder-32B better than Qwen3.5-Flash?

Qwen3.5-Flash is the stronger model overall, scoring 42.3 to 32.9 on the Noometry Index.

### Which is cheaper, Qwen2.5-Coder-32B or Qwen3.5-Flash?

Qwen3.5-Flash is cheaper. It lists at $0.10 per million input tokens and $0.40 per million output tokens; Qwen2.5-Coder-32B lists at $0.66 and $1.

### Is Qwen2.5-Coder-32B or Qwen3.5-Flash better for coding?

Qwen3.5-Flash scores higher on coding benchmarks: 33.9 versus 22.4 in the Noometry coding category.

### Which has the bigger context window?

Qwen3.5-Flash does, with 1M tokens against 33K.

### How many benchmarks do Qwen2.5-Coder-32B and Qwen3.5-Flash share?

13 benchmarks have published results for both models. Qwen2.5-Coder-32B has 31 scored results on Noometry and Qwen3.5-Flash has 32.